Evidence map›Paper›PMID 36846049›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2023

To Investigate the Potential Mechanism of Huanglian Jiangtang Formula Lowering Blood Sugar in View of Network Pharmacology and Molecular Docking Technology.

Fang Xu Li, Ziting Zhou, Cheng Lu, Guoming Pang, Zhigang Lu

Abstract read
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Article in Evidence-based complementary and alternative medicine : eCAM, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Fang Xu LiHospital of Traditional Chinese Medicine, Kaifeng 475000, Henan, China.ORCID https://orcid.org/0000-0001-5233-9792
Ziting ZhouNanjing University of Traditional Chinese Medicine, Nanjing 210023, Jiangsu, China.
Cheng LuInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.ORCID https://orcid.org/0000-0002-6474-9198
Guoming PangHospital of Traditional Chinese Medicine, Kaifeng 475000, Henan, China.ORCID https://orcid.org/0000-0001-9478-1431
Zhigang LuNanjing University of Traditional Chinese Medicine, Nanjing 210023, Jiangsu, China.ORCID https://orcid.org/0000-0001-6769-3647

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: In view of network pharmacology and molecular docking technology, to explore the targets as well as effect mechanism of the Huanglian Jiangtang formula (including Methods: TCMSP and Batman database (DB) were used to retrieve the chemical components and action targets of drugs; GeneCards, OMIM, TTD, DrugBank, and other databases were applied to screen the disease targets. We used the UniProt DB to annotate the targets before building the drug-compound-target network with Cytoscape 3.9.1. We also exploited the String DB to construct the protein-protein interaction (PPI) network. In addition, the targets for the treatment of type II diabetes were searched in the DrugBank, OMIM, GeneCards, and TTD database; then, we utilized Venn to intersect the key targets for the therapy of type II diabetes and active ingredient targets to obtain common targets. Furthermore, we exploited the common targets using GO and KEGG enrichment analysis method. The common targets and core components were analyzed by molecular docking using the AutoDock software. Results: A total of 61 effective components of this compound were screened out; drugs and type II diabetes have 278 common targets; the PPI network screened core target proteins such as CDKN1A, CDK2, and E2F1 with the help of molecular docking technology; the three main compounds including quercetin, kaempferol, and gamma-aminobutyric acid were obtained. Besides, the key target proteins had excellent binding properties with the main components. The signal pathways of six compound interventions in type II diabetes were mostly related to cancer, cocaine addiction, aminoacyl-tRNA biosynthesis, glycine, serine, threonine metabolism, platinum drug resistance, and other pathways, according to the KEGG enrichment analysis method. Conclusion: In the treatment of diabetes, the Huanglian Jiangtang formula has sorts of properties especially in the aspects of composition, target, and pathway. Its molecular target and mechanism of action may be related to pathways in cancer, cocaine addiction, aminoacyl-tRNA biosynthesis, glycine, serine, threonine metabolism, platinum drug resistance, and other pathways. This conclusion can provide theoretical support and science for further research.

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PMID36846049
PMCPMC9950321

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.